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A New Approach to Clustering and Object Detection with Independent Component Analysis

机译:具有独立成分分析的聚类和目标检测新方法

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摘要

It has previously been suggested that the visual cortex performs a data analysis similar to independent component analysis (ICA). Following this idea we show that an incomplete ICA, applied after filtering, can be used to detect objects in natural scenes. Based on this we show that an incomplete ICA can be used to efficiently cluster independent components. We further apply this algorithm to toy data and a real-world fMRI data example and show that this approach to clustering offers a wide variety of applications.
机译:先前已经提出视觉皮层执行类似于独立成分分析(ICA)的数据分析。遵循这个想法,我们表明在滤波后应用不完整的ICA可以用于检测自然场景中的对象。基于此,我们表明不完整的ICA可用于有效地群集独立组件。我们进一步将此算法应用于玩具数据和真实世界的fMRI数据示例,并表明该聚类方法提供了广泛的应用。

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